Non-invasive imaging technologies allow images of the internal structures of a patient or object to be obtained without performing an invasive procedure on the patient or object. In particular, technologies such as computed tomography (CT) use various physical principals, such as the differential transmission of x-rays through the target volume, to acquire image data and to construct tomographic images (e.g., three-dimensional representations of the interior of the human body or of other imaged structures).
Modern CT systems use a technique known as automated tube current modulation (ATCM) to set the dose operating point for an optimized performance between image quality and radiation dose. Traditionally, ATCM generally adapts the tube current to maintain a constant signal at the image detectors, which results in a constant noise across the whole reconstructed volume. Such a strategy, while generally automated, simply relies on noise (image pixel standard deviation) as a universal image quality index.
However, several key elements of the diagnostic procedure, such as system resolution, noise texture, and task-related information are not effectively modeled when performing ATCM based solely on image noise. Besides, since pixel noise is utilized as the only constraint, the final targeted image quality level is usually based on radiologists' subjective preference of image noise level, which does not offer flexibility towards optimized performance of the diagnostic procedure for different clinical tasks and different radiologists.